Links

Tools

Export citation

Search in Google Scholar

Using the Holey Brick Tree for Spatial data in General Purpose DBMSs

This paper is available in a repository.
This paper is available in a repository.

Full text: Download

Question mark in circle
Preprint: policy unknown
Question mark in circle
Postprint: policy unknown
Question mark in circle
Published version: policy unknown

Abstract

Introduction There is leverage to be gained by bringing spatial data within the purview of general purpose database systems. A spatial access method embedded in a general purpose DBMS would have several advantages [Lom91]: 1. Spatial data could be integrated with other data. Spatial objects are likely to have attributes other than the location of their bounding boxes. These other attributes can be queried using traditional methods. 2. Multiple users (some making updates) would be supported by concurrency algorithms already in place. 3. In case of a system failure, the restart process would be able to recover the database to a consistent state. 4. Robust system utilities for loading data, analyzing performance, producing reports and so forth could be applied. To this end, we have been modifying the hB-tree (or holey Brick tree) [LS90], an efficient multiattribute search structure, for use with the concurrency and recovery systems available in general purpose DBMSs. This wi